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Type 'q()' to quit R. > y <- c(8.2,8.3,8.1,7.4,7.3,7.7,8,8,7.7,6.9,6.6,6.9,7.5,7.9,7.7,6.5,6.1,6.4,6.8,7.1,7.3,7.2,7,7,7,7.3,7.5,7.2,7.7,8,7.9,8,8,7.9,7.9,8,8.1,8.1,8.2,8,8.3,8.5,8.6,8.7,8.7,8.5,8.4,8.5,8.7,8.7,8.6,7.9,8.1,8.2,8.5,8.6,8.5,8.3,8.2,8.7) > x <- c(89.1,82.6,102.7,91.8,94.1,103.1,93.2,91,94.3,99.4,115.7,116.8,99.8,96,115.9,109.1,117.3,109.8,112.8,110.7,100,113.3,122.4,112.5,104.2,92.5,117.2,109.3,106.1,118.8,105.3,106,102,112.9,116.5,114.8,100.5,85.4,114.6,109.9,100.7,115.5,100.7,99,102.3,108.8,105.9,113.2,95.7,80.9,113.9,98.1,102.8,104.7,95.9,94.6,101.6,103.9,110.3,114.1) > par8 = '3' > par7 = '0' > par6 = '0' > par5 = '1' > par4 = '12' > par3 = '0' > par2 = '0' > par1 = '1' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: Wessa P., (2008), Bivariate Granger Causality (v1.0.0) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_grangercausality.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric > par1 <- as.numeric(par1) > par2 <- as.numeric(par2) > par3 <- as.numeric(par3) > par4 <- as.numeric(par4) > par5 <- as.numeric(par5) > par6 <- as.numeric(par6) > par7 <- as.numeric(par7) > par8 <- as.numeric(par8) > ox <- x > oy <- y > if (par1 == 0) { + x <- log(x) + } else { + x <- (x ^ par1 - 1) / par1 + } > if (par5 == 0) { + y <- log(y) + } else { + y <- (y ^ par5 - 1) / par5 + } > if (par2 > 0) x <- diff(x,lag=1,difference=par2) > if (par6 > 0) y <- diff(y,lag=1,difference=par6) > if (par3 > 0) x <- diff(x,lag=par4,difference=par3) > if (par7 > 0) y <- diff(y,lag=par4,difference=par7) > x [1] 88.1 81.6 101.7 90.8 93.1 102.1 92.2 90.0 93.3 98.4 114.7 115.8 [13] 98.8 95.0 114.9 108.1 116.3 108.8 111.8 109.7 99.0 112.3 121.4 111.5 [25] 103.2 91.5 116.2 108.3 105.1 117.8 104.3 105.0 101.0 111.9 115.5 113.8 [37] 99.5 84.4 113.6 108.9 99.7 114.5 99.7 98.0 101.3 107.8 104.9 112.2 [49] 94.7 79.9 112.9 97.1 101.8 103.7 94.9 93.6 100.6 102.9 109.3 113.1 > y [1] 7.2 7.3 7.1 6.4 6.3 6.7 7.0 7.0 6.7 5.9 5.6 5.9 6.5 6.9 6.7 5.5 5.1 5.4 5.8 [20] 6.1 6.3 6.2 6.0 6.0 6.0 6.3 6.5 6.2 6.7 7.0 6.9 7.0 7.0 6.9 6.9 7.0 7.1 7.1 [39] 7.2 7.0 7.3 7.5 7.6 7.7 7.7 7.5 7.4 7.5 7.7 7.7 7.6 6.9 7.1 7.2 7.5 7.6 7.5 [58] 7.3 7.2 7.7 > (gyx <- grangertest(y ~ x, order=par8)) Granger causality test Model 1: ~ Lags(, 1:3) + Lags(, 1:3) Model 2: ~ Lags(, 1:3) Res.Df Df F Pr(>F) 1 50 2 53 -3 12.429 3.424e-06 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > (gxy <- grangertest(x ~ y, order=par8)) Granger causality test Model 1: ~ Lags(, 1:3) + Lags(, 1:3) Model 2: ~ Lags(, 1:3) Res.Df Df F Pr(>F) 1 50 2 53 -3 2.9162 0.04318 * --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > postscript(file="/var/www/html/rcomp/tmp/12mtp1260377883.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow=c(2,1)) > (r <- ccf(ox,oy,main='Cross Correlation Function (raw data)',ylab='CCF',xlab='Lag (k)')) Autocorrelations of series 'X', by lag -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 0.383 0.203 0.216 0.213 0.224 0.308 0.151 0.003 -0.125 -0.154 -0.053 -3 -2 -1 0 1 2 3 4 5 6 7 0.061 -0.050 -0.310 -0.323 -0.305 -0.207 -0.118 -0.179 -0.316 -0.416 -0.389 8 9 10 11 12 13 14 -0.233 -0.076 -0.124 -0.309 -0.290 -0.209 -0.109 > (r <- ccf(x,y,main='Cross Correlation Function (transformed and differenced)',ylab='CCF',xlab='Lag (k)')) Autocorrelations of series 'X', by lag -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 0.383 0.203 0.216 0.213 0.224 0.308 0.151 0.003 -0.125 -0.154 -0.053 -3 -2 -1 0 1 2 3 4 5 6 7 0.061 -0.050 -0.310 -0.323 -0.305 -0.207 -0.118 -0.179 -0.316 -0.416 -0.389 8 9 10 11 12 13 14 -0.233 -0.076 -0.124 -0.309 -0.290 -0.209 -0.109 > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2i29z1260377883.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow=c(2,1)) > acf(ox,lag.max=round(length(x)/2),main='ACF of x (raw)') > acf(x,lag.max=round(length(x)/2),main='ACF of x (transformed and differenced)') > par(op) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/3sq5c1260377883.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow=c(2,1)) > acf(oy,lag.max=round(length(y)/2),main='ACF of y (raw)') > acf(y,lag.max=round(length(y)/2),main='ACF of y (transformed and differenced)') > par(op) > dev.off() null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Granger Causality Test: Y = f(X)',5,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Model',header=TRUE) > a<-table.element(a,'Res.DF',header=TRUE) > a<-table.element(a,'Diff. DF',header=TRUE) > a<-table.element(a,'F',header=TRUE) > a<-table.element(a,'p-value',header=TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Complete model',header=TRUE) > a<-table.element(a,gyx$Res.Df[1]) > a<-table.element(a,'') > a<-table.element(a,'') > a<-table.element(a,'') > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Reduced model',header=TRUE) > a<-table.element(a,gyx$Res.Df[2]) > a<-table.element(a,gyx$Df[2]) > a<-table.element(a,gyx$F[2]) > a<-table.element(a,gyx$Pr[2]) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/4ngik1260377883.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Granger Causality Test: X = f(Y)',5,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Model',header=TRUE) > a<-table.element(a,'Res.DF',header=TRUE) > a<-table.element(a,'Diff. DF',header=TRUE) > a<-table.element(a,'F',header=TRUE) > a<-table.element(a,'p-value',header=TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Complete model',header=TRUE) > a<-table.element(a,gxy$Res.Df[1]) > a<-table.element(a,'') > a<-table.element(a,'') > a<-table.element(a,'') > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Reduced model',header=TRUE) > a<-table.element(a,gxy$Res.Df[2]) > a<-table.element(a,gxy$Df[2]) > a<-table.element(a,gxy$F[2]) > a<-table.element(a,gxy$Pr[2]) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/5rbkg1260377883.tab") > > system("convert tmp/12mtp1260377883.ps tmp/12mtp1260377883.png") > system("convert tmp/2i29z1260377883.ps tmp/2i29z1260377883.png") > system("convert tmp/3sq5c1260377883.ps tmp/3sq5c1260377883.png") > > > proc.time() user system elapsed 0.926 0.498 1.407